Certain graphic manipulation applications allow two-dimensional (“2D”) images, such as decals, to be applied to three-dimensional (“3D”) models. Applying a 2D image to a 3D model can add a desired style, texture, or other aesthetic quality to the 3D model. For instance, as depicted in FIG. 1, an image application process 106 is used to apply a 2D image 104 (e.g., a decal with the title “Soda-flavored pop!”) to a 3D model 102 depicting a soda can. The image application process 106 overlays pixels from the 2D image 104 on top of the cylindrical side of the 3D model 102, resulting in a stylized 3D model 108.
Different existing techniques facilitate these types of image application processes. For instance, parameterization techniques create mappings between pixels of the 2D image and points along a mesh that defines a 3D model. These methods allow image content from a given pixel to be applied to a corresponding point along the mesh.
But existing parameterization methods presents several limitations. One limitation is quality. Some existing parameterization techniques assume an isometric map (i.e., a distortion-free map) exists between the 2D image and a target mesh region to which the 2D image is applied. But if the target mesh region cannot be flattened without distorting features of the mesh, such an isometric map does not exist and the applied 2D image includes distortions. Another example of a limitation in existing techniques is a lack of extensibility. For instance, existing parameterization techniques cannot be easily customized to specific insertion tasks, such as aligning the boundaries of a 2D image to lines or points on the 3D mesh surface. Furthermore, the computation time for existing parameterization techniques can take a long time for larger meshes, making it hard to create interactive decal-placement experiences.
Thus, existing solutions may involve disadvantages for reasons such as (but not limited to) those described above.